activity
20152024
most citedA review of homomorphic encryption and software tools for encrypted statistical machine learning

58 citations · 228 across the 22 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

stat.ML2020★ 37 cited

Explicit Regularisation in Gaussian Noise Injections

Alexander Camuto, Matthew Willetts, Umut Şimşekli +2

We study the regularisation induced in neural networks by Gaussian noise injections (GNIs). Though such injections have been extensively studied when applied to data, there have be…

stat.ML2020★ 2 cited

Towards a Theoretical Understanding of the Robustness of Variational Autoencoders

Alexander Camuto, Matthew Willetts, Stephen Roberts +2

We make inroads into understanding the robustness of Variational Autoencoders (VAEs) to adversarial attacks and other input perturbations. While previous work has developed algorit…

stat.ML2020★ 1 cited

Relaxed-Responsibility Hierarchical Discrete VAEs

Matthew Willetts, Xenia Miscouridou, Stephen Roberts +1

Successfully training Variational Autoencoders (VAEs) with a hierarchy of discrete latent variables remains an area of active research. Vector-Quantised VAEs are a powerful approac…

cs.LG2020★ 18 cited

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift

Sheheryar Zaidi, Arber Zela, Thomas Elsken +3

Ensembles of neural networks achieve superior performance compared to stand-alone networks in terms of accuracy, uncertainty calibration and robustness to dataset shift. \emph{Deep…

cs.LG2020★ 1 cited

Learning Bijective Feature Maps for Linear ICA

Alexander Camuto, Matthew Willetts, Brooks Paige +2

Separating high-dimensional data like images into independent latent factors, i.e independent component analysis (ICA), remains an open research problem. As we show, existing proba…